167 phd-mathematical-modelling-population-modelling Postdoctoral positions at University of Oxford
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Postdoctoral Research Associate in Sum-Frequency Generation Microscopy of Biomolecular Self-Assembly
structure formed in model phospholipid membranes. Beyond this, the project aims to expand such investigations to bilayer systems and also investigate the influence of lipid-protein and protein-protein
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to reconstruct the tree-of-life on Earth, it allows us to reveal how biological function has evolved and is distributed on this tree, and it is the foundation that enables us to use model organisms
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analyses to patient-derived samples and disease models. Working closely with a dynamic and multidisciplinary team of clinicians and scientists, they will help generate and interpret high-resolution datasets
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-defined disease states and is funded by ERC. Find out more about the Aye research and group at: https://www.chem.ox.ac.uk/people/yimon-aye About you Applicants must hold a PhD in Chemistry, Chemical Biology
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of research projects on human immunity against bacterial and viral infections using human challenge models. You will support the research of Post-Doctoral Scientists, whilst obtaining training in working
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developing characterisations of network models and interactions with methods in statistical machine learning. The post holder provides guidance to junior members of the research group including project
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new understanding to bridge the gap between existing models for well-established hard and soft semiconductors. The resulting discoveries will provide a blueprint for light-harvesting materials, guiding
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lowland river chemistry. Ultimately, these experiments will be used to parameterise calcite precipitation rate equations and empirical rate constants to inform catchment-scale modelling of ERW practices and
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renewable award. You will lead a programme of research in the molecular mechanisms of cardiovascular disease, that may include a range of approaches including targeted genetic murine models, primary cell
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systems modelling including technical knowledge (e.g., in data science, input-output modelling, applied economic modelling, environmental and ecological assessments, GIS, comparative risk assessments), as